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Pubmed Article
Metaphor identification in large texts corpora.
PUBLISHED: 01-01-2013
Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpora of Reuters and the New York Times articles. The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus.
Authors: Gary E. Raney, Spencer J. Campbell, Joanna C. Bovee.
Published: 01-10-2014
The present article describes how to use eye tracking methodologies to study the cognitive processes involved in text comprehension. Measuring eye movements during reading is one of the most precise methods for measuring moment-by-moment (online) processing demands during text comprehension. Cognitive processing demands are reflected by several aspects of eye movement behavior, such as fixation duration, number of fixations, and number of regressions (returning to prior parts of a text). Important properties of eye tracking equipment that researchers need to consider are described, including how frequently the eye position is measured (sampling rate), accuracy of determining eye position, how much head movement is allowed, and ease of use. Also described are properties of stimuli that influence eye movements that need to be controlled in studies of text comprehension, such as the position, frequency, and length of target words. Procedural recommendations related to preparing the participant, setting up and calibrating the equipment, and running a study are given. Representative results are presented to illustrate how data can be evaluated. Although the methodology is described in terms of reading comprehension, much of the information presented can be applied to any study in which participants read verbal stimuli.
26 Related JoVE Articles!
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Determining heat and mechanical pain threshold in inflamed skin of human subjects
Authors: Martin S Angst, Martha Tingle, Nicholas G Phillips, Brendan Carvalho.
Institutions: Stanford University School of Medicine.
In a previous article in the Journal of Visualized Experiments we have demonstrated skin microdialysis techniques for the collection of tissue-specific nociceptive and inflammatory biochemicals in humans. In this article we will show pain-testing paradigms that are often used in tandem with microdialysis procedures. Combining pain tests with microdialysis provides the critical link between behavioral and biochemical data that allows identifying key biochemicals responsible for generating and propagating pain. Two models of evoking pain in inflamed skin of human study participants are shown. The first model evokes pain with aid of heat stimuli. Heat evoked pain as described here is predominantly mediated by small, non-myelinated peripheral nociceptive nerve fibers (C-fibers). The second model evokes pain via punctuated pressure stimuli. Punctuated pressure evoked pain is predominantly mediated by small, myelinated peripheral nociceptive nerve fibers (A-delta fibers). The two models are mechanistically distinct and independently examine nociceptive processing by the two major peripheral nerve fiber populations involved in pain signaling. Heat pain is evoked with aid of the TSA II, a commercially available thermo-sensory analyzer (Medoc Advanced Medical Systems, Durham, NC). Stimulus configuration and delivery is handled with aid of specific software. Thermodes vary in size and shape but in principle consist of a metal plate that can be heated or cooled at various rates and for different periods of time. Algorithms assessing heat-evoked pain are manifold. In the experiments shown here, study participants are asked to indicate at what point they start experiencing pain while the thermode in contact with skin is heated at a predetermined rate starting at a temperature that does not evoke pain. The thermode temperature at which a subject starts experiencing pain constitutes the heat pain threshold. Mechanical pain is evoked with punctuated probes. Such probes are commercially available from several manufacturers (von Frey hairs). However, the accuracy of von Frey hairs has been criticized and many investigators use custom made punctuated pressure probes. In the experiments shown here eight custom-made punctuated probes of different weights are applied in consecutive order, a procedure called up-down algorithm, to identify perceptional deflection points, i.e., a change from feeling no pain to feeling pain or vice versa. The average weight causing a perceptional deflection constitutes the mechanical pain threshold.
Medicine, Issue 23, Experimental pain, experimental inflammation, human, skin, heat stimuli, mechanical stimuli, pain threshold, psychophysics, non-myelinated nociceptive nerve fiber, small myelinated nociceptive nerve fiber
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Test Samples for Optimizing STORM Super-Resolution Microscopy
Authors: Daniel J. Metcalf, Rebecca Edwards, Neelam Kumarswami, Alex E. Knight.
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Authors: Philippe Pérot, Valérie Cheynet, Myriam Decaussin-Petrucci, Guy Oriol, Nathalie Mugnier, Claire Rodriguez-Lafrasse, Alain Ruffion, François Mallet.
Institutions: Joint Unit Hospices de Lyon-bioMérieux, BioMérieux, Hospices Civils de Lyon, Lyon 1 University, BioMérieux, Hospices Civils de Lyon, Hospices Civils de Lyon.
The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1).
Medicine, Issue 81, Cancer Biology, Genetics, Molecular Biology, Prostate, Retroviridae, Biomarkers, Pharmacological, Tumor Markers, Biological, Prostatectomy, Microarray Analysis, Gene Expression, Diagnosis, Human Endogenous Retroviruses, HERV, microarray, Transcriptome, prostate cancer, Affymetrix
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Transabdominal Ultrasound for Pregnancy Diagnosis in Reeves' Muntjac Deer
Authors: Kelly D. Walton, Erin McNulty, Amy V. Nalls, Candace K. Mathiason.
Institutions: Colorado State University.
Reeves' muntjac deer (Muntiacus reevesi) are a small cervid species native to southeast Asia, and are currently being investigated as a potential model of prion disease transmission and pathogenesis. Vertical transmission is an area of interest among researchers studying infectious diseases, including prion disease, and these investigations require efficient methods for evaluating the effects of maternal infection on reproductive performance. Ultrasonographic examination is a well-established tool for diagnosing pregnancy and assessing fetal health in many animal species1-7, including several species of farmed cervids8-19, however this technique has not been described in Reeves' muntjac deer. Here we describe the application of transabdominal ultrasound to detect pregnancy in muntjac does and to evaluate fetal growth and development throughout the gestational period. Using this procedure, pregnant animals were identified as early as 35 days following doe-buck pairing and this was an effective means to safely monitor the pregnancy at regular intervals. Future goals of this work will include establishing normal fetal measurement references for estimation of gestational age, determining sensitivity and specificity of the technique for diagnosing pregnancy at various stages of gestation, and identifying variations in fetal growth and development under different experimental conditions.
Medicine, Issue 83, Ultrasound, Reeves' muntjac deer, Muntiacus reevesi, fetal development, fetal growth, captive cervids
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs. LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors. While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
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Spatial Separation of Molecular Conformers and Clusters
Authors: Daniel Horke, Sebastian Trippel, Yuan-Pin Chang, Stephan Stern, Terry Mullins, Thomas Kierspel, Jochen Küpper.
Institutions: CFEL, DESY, University of Hamburg, University of Hamburg.
Gas-phase molecular physics and physical chemistry experiments commonly use supersonic expansions through pulsed valves for the production of cold molecular beams. However, these beams often contain multiple conformers and clusters, even at low rotational temperatures. We present an experimental methodology that allows the spatial separation of these constituent parts of a molecular beam expansion. Using an electric deflector the beam is separated by its mass-to-dipole moment ratio, analogous to a bender or an electric sector mass spectrometer spatially dispersing charged molecules on the basis of their mass-to-charge ratio. This deflector exploits the Stark effect in an inhomogeneous electric field and allows the separation of individual species of polar neutral molecules and clusters. It furthermore allows the selection of the coldest part of a molecular beam, as low-energy rotational quantum states generally experience the largest deflection. Different structural isomers (conformers) of a species can be separated due to the different arrangement of functional groups, which leads to distinct dipole moments. These are exploited by the electrostatic deflector for the production of a conformationally pure sample from a molecular beam. Similarly, specific cluster stoichiometries can be selected, as the mass and dipole moment of a given cluster depends on the degree of solvation around the parent molecule. This allows experiments on specific cluster sizes and structures, enabling the systematic study of solvation of neutral molecules.
Physics, Issue 83, Chemical Physics, Physical Chemistry, Molecular Physics, Molecular beams, Laser Spectroscopy, Clusters
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Utero-tubal Embryo Transfer and Vasectomy in the Mouse Model
Authors: Pablo Bermejo-Alvarez, Ki-Eun Park, Bhanu P. Telugu.
Institutions: United States Department of Agriculture, University of Maryland.
The transfer of preimplantation embryos to a surrogate female is a required step for the production of genetically modified mice or to study the effects of epigenetic alterations originated during preimplantation development on subsequent fetal development and adult health. The use of an effective and consistent embryo transfer technique is crucial to enhance the generation of genetically modified animals and to determine the effect of different treatments on implantation rates and survival to term. Embryos at the blastocyst stage are usually transferred by uterine transfer, performing a puncture in the uterine wall to introduce the embryo manipulation pipette. The orifice performed in the uterus does not close after the pipette has been withdrawn, and the embryos can outflow to the abdominal cavity due to the positive pressure of the uterus. The puncture can also produce a hemorrhage that impairs implantation, blocks the transfer pipette and may affect embryo development, especially when embryos without zona are transferred. Consequently, this technique often results in very variable and overall low embryo survival rates. Avoiding these negative effects, utero-tubal embryo transfer take advantage of the utero-tubal junction as a natural barrier that impedes embryo outflow and avoid the puncture of the uterine wall. Vasectomized males are required for obtaining pseudopregnant recipients. A technique to perform vasectomy is described as a complement to the utero-tubal embryo transfer.
Basic Protocols, Issue 84, blastocyst, chimera, lentivirus, uterine transfer, oviductal transfer, utero-tubal transfer
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
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High-speed Particle Image Velocimetry Near Surfaces
Authors: Louise Lu, Volker Sick.
Institutions: University of Michigan.
Multi-dimensional and transient flows play a key role in many areas of science, engineering, and health sciences but are often not well understood. The complex nature of these flows may be studied using particle image velocimetry (PIV), a laser-based imaging technique for optically accessible flows. Though many forms of PIV exist that extend the technique beyond the original planar two-component velocity measurement capabilities, the basic PIV system consists of a light source (laser), a camera, tracer particles, and analysis algorithms. The imaging and recording parameters, the light source, and the algorithms are adjusted to optimize the recording for the flow of interest and obtain valid velocity data. Common PIV investigations measure two-component velocities in a plane at a few frames per second. However, recent developments in instrumentation have facilitated high-frame rate (> 1 kHz) measurements capable of resolving transient flows with high temporal resolution. Therefore, high-frame rate measurements have enabled investigations on the evolution of the structure and dynamics of highly transient flows. These investigations play a critical role in understanding the fundamental physics of complex flows. A detailed description for performing high-resolution, high-speed planar PIV to study a transient flow near the surface of a flat plate is presented here. Details for adjusting the parameter constraints such as image and recording properties, the laser sheet properties, and processing algorithms to adapt PIV for any flow of interest are included.
Physics, Issue 76, Mechanical Engineering, Fluid Mechanics, flow measurement, fluid heat transfer, internal flow in turbomachinery (applications), boundary layer flow (general), flow visualization (instrumentation), laser instruments (design and operation), Boundary layer, micro-PIV, optical laser diagnostics, internal combustion engines, flow, fluids, particle, velocimetry, visualization
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Isolation of Sensory Neurons of Aplysia californica for Patch Clamp Recordings of Glutamatergic Currents
Authors: Lynne A. Fieber, Stephen L. Carlson, Andrew T. Kempsell, Justin B. Greer, Michael C. Schmale.
Institutions: University of Miami.
The marine gastropod mollusk Aplysia californica has a venerable history as a model of nervous system function, with particular significance in studies of learning and memory. The typical preparations for such studies are ones in which the sensory and motoneurons are left intact in a minimally dissected animal, or a technically elaborate neuronal co-culture of individual sensory and motoneurons. Less common is the isolated neuronal preparation in which small clusters of nominally homogeneous neurons are dissociated into single cells in short term culture. Such isolated cells are useful for the biophysical characterization of ion currents using patch clamp techniques, and targeted modulation of these conductances. A protocol for preparing such cultures is described. The protocol takes advantage of the easily identifiable glutamatergic sensory neurons of the pleural and buccal ganglia, and describes their dissociation and minimal maintenance in culture for several days without serum.
Neuroscience, Issue 77, Neurobiology, Anatomy, Physiology, Cellular Biology, Molecular Biology, Environmental Sciences, Marine Biology, Receptors, Neurophysiology, Neurotransmitter, Neurotransmitter Agents, Patch Clamp Recordings, Primary Cell Culture, Electrophysiology, L-Glutamate, NMDA, D-Aspartate, dissection, ganglia, buccal ganglion, neurons, invertebrate, Aplysia californica, california sea slug, mollusk, animal model
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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Making Sense of Listening: The IMAP Test Battery
Authors: Johanna G. Barry, Melanie A. Ferguson, David R. Moore.
Institutions: MRC Institute of Hearing Research, National Biomedical Research Unit in Hearing.
The ability to hear is only the first step towards making sense of the range of information contained in an auditory signal. Of equal importance are the abilities to extract and use the information encoded in the auditory signal. We refer to these as listening skills (or auditory processing AP). Deficits in these skills are associated with delayed language and literacy development, though the nature of the relevant deficits and their causal connection with these delays is hotly debated. When a child is referred to a health professional with normal hearing and unexplained difficulties in listening, or associated delays in language or literacy development, they should ideally be assessed with a combination of psychoacoustic (AP) tests, suitable for children and for use in a clinic, together with cognitive tests to measure attention, working memory, IQ, and language skills. Such a detailed examination needs to be relatively short and within the technical capability of any suitably qualified professional. Current tests for the presence of AP deficits tend to be poorly constructed and inadequately validated within the normal population. They have little or no reference to the presenting symptoms of the child, and typically include a linguistic component. Poor performance may thus reflect problems with language rather than with AP. To assist in the assessment of children with listening difficulties, pediatric audiologists need a single, standardized child-appropriate test battery based on the use of language-free stimuli. We present the IMAP test battery which was developed at the MRC Institute of Hearing Research to supplement tests currently used to investigate cases of suspected AP deficits. IMAP assesses a range of relevant auditory and cognitive skills and takes about one hour to complete. It has been standardized in 1500 normally-hearing children from across the UK, aged 6-11 years. Since its development, it has been successfully used in a number of large scale studies both in the UK and the USA. IMAP provides measures for separating out sensory from cognitive contributions to hearing. It further limits confounds due to procedural effects by presenting tests in a child-friendly game-format. Stimulus-generation, management of test protocols and control of test presentation is mediated by the IHR-STAR software platform. This provides a standardized methodology for a range of applications and ensures replicable procedures across testers. IHR-STAR provides a flexible, user-programmable environment that currently has additional applications for hearing screening, mapping cochlear implant electrodes, and academic research or teaching.
Neuroscience, Issue 44, Listening skills, auditory processing, auditory psychophysics, clinical assessment, child-friendly testing
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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Trajectory Data Analyses for Pedestrian Space-time Activity Study
Authors: Feng Qi, Fei Du.
Institutions: Kean University, University of Wisconsin-Madison.
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4. Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling. The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5 involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6 and density volume rendering7. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.
Environmental Sciences, Issue 72, Computer Science, Behavior, Infectious Diseases, Geography, Cartography, Data Display, Disease Outbreaks, cartography, human behavior, Trajectory data, space-time activity, GPS, GIS, ArcGIS, spatiotemporal analysis, visualization, segmentation, density surface, density volume, exploratory data analysis, modelling
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Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind
Authors: Erin C. Connors, Lindsay A. Yazzolino, Jaime Sánchez, Lotfi B. Merabet.
Institutions: Massachusetts Eye and Ear Infirmary, Harvard Medical School, University of Chile .
Audio-based Environment Simulator (AbES) is virtual environment software designed to improve real world navigation skills in the blind. Using only audio based cues and set within the context of a video game metaphor, users gather relevant spatial information regarding a building's layout. This allows the user to develop an accurate spatial cognitive map of a large-scale three-dimensional space that can be manipulated for the purposes of a real indoor navigation task. After game play, participants are then assessed on their ability to navigate within the target physical building represented in the game. Preliminary results suggest that early blind users were able to acquire relevant information regarding the spatial layout of a previously unfamiliar building as indexed by their performance on a series of navigation tasks. These tasks included path finding through the virtual and physical building, as well as a series of drop off tasks. We find that the immersive and highly interactive nature of the AbES software appears to greatly engage the blind user to actively explore the virtual environment. Applications of this approach may extend to larger populations of visually impaired individuals.
Medicine, Issue 73, Behavior, Neuroscience, Anatomy, Physiology, Neurobiology, Ophthalmology, Psychology, Behavior and Behavior Mechanisms, Technology, Industry, virtual environments, action video games, blind, audio, rehabilitation, indoor navigation, spatial cognitive map, Audio-based Environment Simulator, virtual reality, cognitive psychology, clinical techniques
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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Preparation of a Blood Culture Pellet for Rapid Bacterial Identification and Antibiotic Susceptibility Testing
Authors: Antony Croxatto, Guy Prod'hom, Christian Durussel, Gilbert Greub.
Institutions: University Hospital Center and University of Lausanne.
Bloodstream infections and sepsis are a major cause of morbidity and mortality. The successful outcome of patients suffering from bacteremia depends on a rapid identification of the infectious agent to guide optimal antibiotic treatment. The analysis of Gram stains from positive blood culture can be rapidly conducted and already significantly impact the antibiotic regimen. However, the accurate identification of the infectious agent is still required to establish the optimal targeted treatment. We present here a simple and fast bacterial pellet preparation from a positive blood culture that can be used as a sample for several essential downstream applications such as identification by MALDI-TOF MS, antibiotic susceptibility testing (AST) by disc diffusion assay or automated AST systems and by automated PCR-based diagnostic testing. The performance of these different identification and AST systems applied directly on the blood culture bacterial pellets is very similar to the performance normally obtained from isolated colonies grown on agar plates. Compared to conventional approaches, the rapid acquisition of a bacterial pellet significantly reduces the time to report both identification and AST. Thus, following blood culture positivity, identification by MALDI-TOF can be reported within less than 1 hr whereas results of AST by automated AST systems or disc diffusion assays within 8 to 18 hr, respectively. Similarly, the results of a rapid PCR-based assay can be communicated to the clinicians less than 2 hr following the report of a bacteremia. Together, these results demonstrate that the rapid preparation of a blood culture bacterial pellet has a significant impact on the identification and AST turnaround time and thus on the successful outcome of patients suffering from bloodstream infections.
Immunology, Issue 92, blood culture, bacteriology, identification, antibiotic susceptibility testing, MALDI-TOF MS.
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Determining 3D Flow Fields via Multi-camera Light Field Imaging
Authors: Tadd T. Truscott, Jesse Belden, Joseph R. Nielson, David J. Daily, Scott L. Thomson.
Institutions: Brigham Young University, Naval Undersea Warfare Center, Newport, RI.
In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and observed phenomena in fluid flows. Thus, a need exists for an accessible method capable of resolving three-dimensional (3D) data sets for a range of problems. We present a novel technique for performing quantitative 3D imaging of many types of flow fields. The 3D technique enables investigation of complicated velocity fields and bubbly flows. Measurements of these types present a variety of challenges to the instrument. For instance, optically dense bubbly multiphase flows cannot be readily imaged by traditional, non-invasive flow measurement techniques due to the bubbles occluding optical access to the interior regions of the volume of interest. By using Light Field Imaging we are able to reparameterize images captured by an array of cameras to reconstruct a 3D volumetric map for every time instance, despite partial occlusions in the volume. The technique makes use of an algorithm known as synthetic aperture (SA) refocusing, whereby a 3D focal stack is generated by combining images from several cameras post-capture 1. Light Field Imaging allows for the capture of angular as well as spatial information about the light rays, and hence enables 3D scene reconstruction. Quantitative information can then be extracted from the 3D reconstructions using a variety of processing algorithms. In particular, we have developed measurement methods based on Light Field Imaging for performing 3D particle image velocimetry (PIV), extracting bubbles in a 3D field and tracking the boundary of a flickering flame. We present the fundamentals of the Light Field Imaging methodology in the context of our setup for performing 3DPIV of the airflow passing over a set of synthetic vocal folds, and show representative results from application of the technique to a bubble-entraining plunging jet.
Physics, Issue 73, Mechanical Engineering, Fluid Mechanics, Engineering, synthetic aperture imaging, light field, camera array, particle image velocimetry, three dimensional, vector fields, image processing, auto calibration, vocal chords, bubbles, flow, fluids
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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Authors: Sergey Rabotyagov, Todd Campbell, Adriana Valcu, Philip Gassman, Manoj Jha, Keith Schilling, Calvin Wolter, Catherine Kling.
Institutions: University of Washington, Iowa State University, North Carolina A&T University, Iowa Geological and Water Survey.
Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods3,4,9,10,13-15,17-19,22,23,25. In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model7 with a multiobjective evolutionary algorithm SPEA226, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.
Environmental Sciences, Issue 70, Plant Biology, Civil Engineering, Forest Sciences, Water quality, multiobjective optimization, evolutionary algorithms, cost efficiency, agriculture, development
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Authors: Viktor Martyanov, Robert H. Gross.
Institutions: Dartmouth College.
SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference1. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data1. In this article, we utilize a web version of SCOPE2 to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs3,4 and has been used in other studies5-8. The three algorithms that comprise SCOPE are BEAM9, which finds non-degenerate motifs (ACCGGT), PRISM10, which finds degenerate motifs (ASCGWT), and SPACER11, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail1,2,9-11.
Genetics, Issue 51, gene regulation, computational biology, algorithm, promoter sequence motif
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Semi-automated Optical Heartbeat Analysis of Small Hearts
Authors: Karen Ocorr, Martin Fink, Anthony Cammarato, Sanford I. Bernstein, Rolf Bodmer.
Institutions: The Sanford Burnham Institute for Medical Research, The Sanford Burnham Institute for Medical Research, San Diego State University.
We have developed a method for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts (Fink, et. al., 2009). Our Semi-automatic Optical Heartbeat Analysis (SOHA) uses a novel movement detection algorithm that is able to detect cardiac movements associated with individual contractile and relaxation events. The program provides a host of physiologically relevant readouts including systolic and diastolic intervals, heart rate, as well as qualitative and quantitative measures of heartbeat arrhythmicity. The program also calculates heart diameter measurements during both diastole and systole from which fractional shortening and fractional area changes are calculated. Output is provided as a digital file compatible with most spreadsheet programs. Measurements are made for every heartbeat in a record increasing the statistical power of the output. We demonstrate each of the steps where user input is required and show the application of our methodology to the analysis of heart function in all three genetically tractable heart models.
Physiology, Issue 31, Drosophila, zebrafish, mouse, heart, myosin, dilated, restricted, cardiomyopathy, KCNQ, movement detection
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.